| Literature DB >> 32306836 |
Subramanian Boopathi1, Adolfo B Poma2, Ponmalai Kolandaivel3.
Abstract
In the past two decades, the world has faced several infectious disease outbreaks. Ebola, Influenza A (H1N1), SARS, MERS, and Zika virus have had a massive global impact in terms of economic disruption, the strain on local and global public health. Most recently, the global outbreak of novel coronavirus 2019 (SARS-CoV-2) that causes COVID-19 is a newly discovered virus from the coronavirus family in Wuhan city, China, known to be a great threat to the public health systems. As of 15 April 2020, The Johns Hopkins University estimated that the COVID-19 affected more than two million people, resulting in a death toll above 130,000 around the world. Infected people in Europe and America correspond about 40% and 30% of the total reported cases respectively. At this moment only few Asian countries have controlled the disease, but a second wave of new infections is expected. Predicting inhibitor and target to the COVID-19 is an urgent need to protect human from the disease. Therefore, a protocol to identify anti-COVID-19 candidate based on computer-aided drug design is urgently needed. Thousands of compounds including approved drugs and drugs in the clinical trial are available in the literature. In practice, experimental techniques can measure the time and space average properties but they cannot be captured the structural variation of the COVID-19 during the interaction of inhibitor. Computer simulation is particularly suitable to complement experiments to elucidate conformational changes at the molecular level which are related to inhibition process of the COVID-19. Therefore, computational simulation is essential tool to elucidate the phenomenon. The structure-based virtual screening computational approach will be used to filter the best drugs from the literature, the investigate the structural variation of COVID-19 with the interaction of the best inhibitor is a fundamental step to design new drugs and vaccines which can combat the coronavirus. This mini-review will address novel coronavirus structure, mechanism of action, and trial test of antiviral drugs in the lab and patients with COVID-19.Entities:
Keywords: ACE2 receptor; COVID-19; Coronavirus; antiviral drugs; computational simulation; coronavirus Spike
Mesh:
Substances:
Year: 2020 PMID: 32306836 PMCID: PMC7196923 DOI: 10.1080/07391102.2020.1758788
Source DB: PubMed Journal: J Biomol Struct Dyn ISSN: 0739-1102
Figure 1.A) Schematic representation of the genome organization and functional domains of S protein for COVID-19. The single-stranded RNA genomes of COVID-19 encode two large genes, the ORF1a and ORF1b genes, which encode 16 non-structural proteins (nsp1–nsp16). The structural genes encode the structural proteins, spike (S), envelope (E), membrane (M), and nucleocapsid (N). The accessory genes denoted in shades of green. The structure of S protein is shown beneath the genome organization. The S protein is consisting of the S1 and S2 subunits. The S1/S2 cleavage sites are highlighted by dotted lines. In the S-protein, cytoplasm domain (CP); fusion peptide (FP); heptad repeat (HR); receptor-binding domain (RBD); signal peptide (SP); transmembrane domain (TM) are shown B) The viral surface proteins, spike, envelope and membrane, are embedded in a lipid bilayer. The single-stranded positive-sense viral RNA is associated with the nucleocapsid protein.
Figure 2.The schematic diagram of the mechanism of COVID-19 entry and viral replication and viral RNA packing in the human cell.
Figure 3.Three-dimensional structure of COVID-19 Mpro (Jin et al., 2020).
Figure 4.Cartoon representation of COVID-19 Mpro with Antiviral inhibitors, Lopinar and N3 highlighted in box.